Mapping self-regulated learning research in mathematics education for quality education: A bibliometric analysis (2016–2025)
DOI:
https://doi.org/10.64268/inspire.v2i1.132Keywords:
Bibliometric Analysis, Mathematics Education, Quality Education, Self-Regulated LearningAbstract
Background: Although Self-Regulated Learning (SRL) has been extensively studied in mathematics education, existing studies primarily report empirical findings, while the intellectual structure, thematic evolution, and emerging research directions of the field remain insufficiently synthesized. This limitation hinders a comprehensive understanding of research development and future priorities.
Aims: This study aims to analyze trends in publications and citations, the most influential authors and journals, co-occurrence patterns of keywords, temporal trends in research topics, and the density of research topics related to SRL in mathematics education to support Quality Education.
Methods: A quantitative bibliometric approach was employed using the Dimensions database. Publications published between 2016 and 2025 were retrieved using the keywords "Self-Regulated Learning" and "Mathematics Education." Of the 181 records identified, 91 journal articles met the predefined inclusion criteria and were analyzed using VOSviewer (version 1.6.20). Performance analysis was conducted to examine publication and citation trends, while science mapping using co-occurrence, overlay, and density visualizations identified the intellectual structure and thematic development of the field.
Result: The results indicate that publications and citations related to SRL in mathematics education have increased during the 2016–2025 period. Furthermore, Tatang Herman and Dadang Juandi were the authors with the highest number of publications three each while the Journal of Physics: Conference Series was the journal with the highest number of publications, totaling six. Co-occurrence analysis identified three interconnected research clusters dominated by motivation, achievement, self-efficacy, engagement, feedback, and learning environment. Overlay visualization revealed a shift from studies emphasizing individual learner characteristics toward technology-supported learning, instructional frameworks, and learning environments. Density visualization showed that achievement, engagement, feedback, and quantitative empirical approaches remain the most intensively studied themes.
Conclusion: This study advances current understanding by identifying emerging themes and research gaps in SRL within mathematics education. The findings provide evidence-based directions for future research integrating pedagogical, psychological, and technological perspectives, while informing the design of innovative mathematics learning.
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